Naslov
TESTING REMOTE SENSING METHODS FOR INVASIVE ALIEN PLANTS Ailanthus altissima AND Amorpha fruticosa

Autori
Jantol, Nela ; Čvrljak, Matko ; Tomljenović, Ivan ; Žiža, Ivona ; Radun, Branimir Zrinka Mesić

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, stručni

Izvornik
4th CROATIAN SYMPOSIUM ON INVASIVE SPECIES with International Participation - Book of Abstracts / - , 2021, 35-35

Skup
4. hrvatski simpozij o invazivnim vrstama = 4th Croatian Symposium on Invasive Species

Mjesto i datum
Zagreb, Hrvatska, 29.11.2021. - 30.11.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Recenziran

Ključne riječi
UAV, LiDAR, eCognition, Sentinel-2, biomass model

Sažetak
Remote sensing is widely used for the vegetation and habitat mapping. Therefore, using remote sensing can be useful for detailed mapping and monitoring dynamics of spread of invasive species. It can supplement research while being affordable and easy to use. Overview with examples of different remote sensing methods in detection of the invasive alien plants (IAP) will be presented. The remote sensing was used to test the possibilities of mapping IAP Ailanthus altissima as part of the development of monitoring program. Two drone surveys were made in Zagreb and Istria in locations with significant coverage with the Ailanthus altissima. Images were processed with Agisoft Metashape Professional program and resulted in 3D models, DEM and multispectral orthomosaics which showed the best detection of the species in Red Edge spectral channel (735nm ± 10nm). In addition, non-supervised automatic classification with eCognition program was tested. Both methods showed that using drone imagery is suitable in projects where IAP has to be detected, especially in bigger or unapproachable areas or detailed spread has to be documented. Second example is related to the estimation of Amorpha fruticosa biomass in Nature Park Lonjsko polje. The biomass estimation was needed for detection of priority areas for its removal and potential use as energy material. The estimation of biomass was based on the interpretation of Sentinel 2 satellite images, LiDAR data and the field measurements in 42 plots. The best biomass model was based on Sentinel 2 data with August 2019 images in Red Edge, NIR and SWIR bands. In conclusion, the remote sensing could be useful in cost-effective detailed detecting and monitoring of IAP as well as various applications at larger scales.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Interdisciplinarne prirodne znanosti

POVEZANOST RADA